Pandas Profiling Report

Dataset statistics

Number of variables	20
Number of observations	53257
Missing cells	0
Missing cells (%)	0.0%
Total size in memory	8.1 MiB
Average record size in memory	160.0 B

Variable types

Numeric	13
Categorical	7

Alerts

`rec_online_8` has constant value "0.0"	Constant
`sum_recharge` is highly correlated with `recharge_frequency` and 4 other fields	High correlation
`recharge_frequency` is highly correlated with `sum_recharge` and 4 other fields	High correlation
`rec_online_10` is highly correlated with `sum_recharge` and 2 other fields	High correlation
`rec_online_15` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`sos_rec_5` is highly correlated with `sum_recharge` and 2 other fields	High correlation
`rec_online_20_b2` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`pct_rec_1190` is highly correlated with `pct_rec_690`	High correlation
`pct_rec_690` is highly correlated with `pct_rec_1190`	High correlation
`sum_recharge` is highly correlated with `recharge_frequency` and 4 other fields	High correlation
`recharge_frequency` is highly correlated with `sum_recharge` and 4 other fields	High correlation
`rec_online_10` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`rec_online_15` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`sos_rec_5` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`rec_online_20_b2` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`pct_rec_1190` is highly correlated with `pct_rec_690`	High correlation
`pct_rec_690` is highly correlated with `pct_rec_1190`	High correlation
`sum_recharge` is highly correlated with `recharge_frequency` and 4 other fields	High correlation
`recharge_frequency` is highly correlated with `sum_recharge` and 4 other fields	High correlation
`rec_online_10` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`rec_online_15` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`sos_rec_5` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`rec_online_20_b2` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`pct_rec_1190` is highly correlated with `pct_rec_690`	High correlation
`pct_rec_690` is highly correlated with `pct_rec_1190`	High correlation
`chip_pre_rec_20` is highly correlated with `rec_online_8`	High correlation
`rec_online_100_b18` is highly correlated with `rec_online_8`	High correlation
`sos_rec_3` is highly correlated with `rec_online_8`	High correlation
`venda` is highly correlated with `rec_online_8`	High correlation
`pct_rec_1190` is highly correlated with `rec_online_8`	High correlation
`rec_online_8` is highly correlated with `chip_pre_rec_20` and 5 other fields	High correlation
`chip_pre_rec_10` is highly correlated with `rec_online_8`	High correlation
`sum_recharge` is highly correlated with `recharge_frequency` and 4 other fields	High correlation
`recharge_frequency` is highly correlated with `sum_recharge` and 5 other fields	High correlation
`rec_online_10` is highly correlated with `recharge_frequency` and 1 other fields	High correlation
`rec_online_15` is highly correlated with `sum_recharge` and 3 other fields	High correlation
`sos_rec_5` is highly correlated with `sum_recharge` and 5 other fields	High correlation
`rec_online_20_b2` is highly correlated with `sum_recharge` and 3 other fields	High correlation
`rec_online_13` is highly correlated with `recharge_frequency` and 1 other fields	High correlation
`rec_online_50_b8` is highly correlated with `sum_recharge`	High correlation
`pct_rec_1190` is highly correlated with `pct_rec_690`	High correlation
`pct_rec_690` is highly correlated with `pct_rec_1190`	High correlation
`rec_online_50_b8` is highly skewed (γ1 = 27.03772441)	Skewed
`pct_rec_690` is highly skewed (γ1 = 30.75651164)	Skewed
`pct_rec_sos_5` is highly skewed (γ1 = 106.1640427)	Skewed
`sum_recharge` has 36396 (68.3%) zeros	Zeros
`recharge_frequency` has 36196 (68.0%) zeros	Zeros
`rec_online_10` has 44846 (84.2%) zeros	Zeros
`rec_online_35_b5` has 52537 (98.6%) zeros	Zeros
`rec_online_15` has 45727 (85.9%) zeros	Zeros
`sos_rec_5` has 45816 (86.0%) zeros	Zeros
`rec_online_20_b2` has 46324 (87.0%) zeros	Zeros
`rec_online_13` has 50701 (95.2%) zeros	Zeros
`rec_online_50_b8` has 52928 (99.4%) zeros	Zeros
`rec_online_30_b4` has 51710 (97.1%) zeros	Zeros
`rec_online_40_b6` has 52780 (99.1%) zeros	Zeros
`pct_rec_690` has 53128 (99.8%) zeros	Zeros
`pct_rec_sos_5` has 53240 (> 99.9%) zeros	Zeros

Reproduction

Analysis started	2022-03-15 15:21:09.861123
Analysis finished	2022-03-15 15:21:28.247916
Duration	18.39 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

sum_recharge
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	431
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	25.64598269

Minimum	0
Maximum	1133
Zeros	36396
Zeros (%)	68.3%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	20
95-th percentile	145
Maximum	1133
Range	1133
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	57.2915604
Coefficient of variation (CV)	2.23393898
Kurtosis	25.77404542
Mean	25.64598269
Median Absolute Deviation (MAD)	0
Skewness	3.832534439
Sum	1365828.1
Variance	3282.322893
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	36396	68.3%
20	1201	2.3%
10	1014	1.9%
15	995	1.9%
30	798	1.5%
40	729	1.4%
60	632	1.2%
35	521	1.0%
45	505	0.9%
50	485	0.9%
Other values (421)	9981	18.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	36396	68.3%
3	1	< 0.1%
5	153	0.3%
6.9	29	0.1%
10	1014	1.9%
11.9	30	0.1%
13	217	0.4%
13.8	6	< 0.1%
15	995	1.9%
18	55	0.1%

Value	Count	Frequency (%)
1133	1	< 0.1%
1130	1	< 0.1%
1041	1	< 0.1%
1025	1	< 0.1%
809	1	< 0.1%
803	1	< 0.1%
756	1	< 0.1%
740	1	< 0.1%
700	1	< 0.1%
679	1	< 0.1%

recharge_frequency
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	65
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.977937173

Minimum	0
Maximum	111
Zeros	36196
Zeros (%)	68.0%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	2
95-th percentile	11
Maximum	111
Range	111
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	4.529962748
Coefficient of variation (CV)	2.290246025
Kurtosis	36.25302536
Mean	1.977937173
Median Absolute Deviation (MAD)	0
Skewness	4.352737132
Sum	105339
Variance	20.52056249
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	36196	68.0%
1	2960	5.6%
2	2412	4.5%
3	2121	4.0%
4	1586	3.0%
5	1183	2.2%
6	1060	2.0%
7	805	1.5%
8	702	1.3%
9	609	1.1%
Other values (55)	3623	6.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	36196	68.0%
1	2960	5.6%
2	2412	4.5%
3	2121	4.0%
4	1586	3.0%
5	1183	2.2%
6	1060	2.0%
7	805	1.5%
8	702	1.3%
9	609	1.1%

Value	Count	Frequency (%)
111	1	< 0.1%
96	1	< 0.1%
89	1	< 0.1%
85	1	< 0.1%
69	1	< 0.1%
66	2	< 0.1%
64	1	< 0.1%
62	3	< 0.1%
61	1	< 0.1%
60	3	< 0.1%

rec_online_10
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	33
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.5946823892

Minimum	0
Maximum	33
Zeros	44846
Zeros (%)	84.2%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	4
Maximum	33
Range	33
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2.03403893
Coefficient of variation (CV)	3.420378621
Kurtosis	36.63970165
Mean	0.5946823892
Median Absolute Deviation (MAD)	0
Skewness	5.289392529
Sum	31671
Variance	4.137314369
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=33)

Value	Count	Frequency (%)
0	44846	84.2%
1	2955	5.5%
2	1538	2.9%
3	963	1.8%
4	674	1.3%
5	453	0.9%
6	347	0.7%
7	261	0.5%
8	257	0.5%
9	197	0.4%
Other values (23)	766	1.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	44846	84.2%
1	2955	5.5%
2	1538	2.9%
3	963	1.8%
4	674	1.3%
5	453	0.9%
6	347	0.7%
7	261	0.5%
8	257	0.5%
9	197	0.4%

Value	Count	Frequency (%)
33	2	< 0.1%
31	1	< 0.1%
30	1	< 0.1%
29	4	< 0.1%
28	2	< 0.1%
27	3	< 0.1%
26	2	< 0.1%
25	3	< 0.1%
24	2	< 0.1%
23	2	< 0.1%

rec_online_35_b5
Real number (ℝ_≥0)

ZEROS

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.02407195298

Minimum	0
Maximum	9
Zeros	52537
Zeros (%)	98.6%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	9
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2447871637
Coefficient of variation (CV)	10.16897814
Kurtosis	268.907612
Mean	0.02407195298
Median Absolute Deviation (MAD)	0
Skewness	14.24979011
Sum	1282
Variance	0.05992075553
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	52537	98.6%
1	399	0.7%
2	169	0.3%
3	107	0.2%
4	20	< 0.1%
5	15	< 0.1%
6	5	< 0.1%
7	3	< 0.1%
9	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	52537	98.6%
1	399	0.7%
2	169	0.3%
3	107	0.2%
4	20	< 0.1%
5	15	< 0.1%
6	5	< 0.1%
7	3	< 0.1%
9	2	< 0.1%

Value	Count	Frequency (%)
9	2	< 0.1%
7	3	< 0.1%
6	5	< 0.1%
5	15	< 0.1%
4	20	< 0.1%
3	107	0.2%
2	169	0.3%
1	399	0.7%
0	52537	98.6%

rec_online_15
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	32
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4019565503

Minimum	0
Maximum	36
Zeros	45727
Zeros (%)	85.9%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	36
Range	36
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.489663929
Coefficient of variation (CV)	3.706032225
Kurtosis	71.88689742
Mean	0.4019565503
Median Absolute Deviation (MAD)	0
Skewness	6.881118575
Sum	21407
Variance	2.21909862
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
0	45727	85.9%
1	3257	6.1%
2	1570	2.9%
3	935	1.8%
4	525	1.0%
5	334	0.6%
6	214	0.4%
7	174	0.3%
8	116	0.2%
9	90	0.2%
Other values (22)	315	0.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	45727	85.9%
1	3257	6.1%
2	1570	2.9%
3	935	1.8%
4	525	1.0%
5	334	0.6%
6	214	0.4%
7	174	0.3%
8	116	0.2%
9	90	0.2%

Value	Count	Frequency (%)
36	1	< 0.1%
35	1	< 0.1%
33	1	< 0.1%
31	1	< 0.1%
30	1	< 0.1%
27	3	< 0.1%
26	1	< 0.1%
25	1	< 0.1%
23	1	< 0.1%
22	2	< 0.1%

sos_rec_5
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	34
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4022382034

Minimum	0
Maximum	48
Zeros	45816
Zeros (%)	86.0%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	3
Maximum	48
Range	48
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.475077451
Coefficient of variation (CV)	3.667173923
Kurtosis	104.882123
Mean	0.4022382034
Median Absolute Deviation (MAD)	0
Skewness	7.549238736
Sum	21422
Variance	2.175853485
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
0	45816	86.0%
1	3048	5.7%
2	1509	2.8%
3	990	1.9%
4	559	1.0%
5	433	0.8%
6	260	0.5%
7	184	0.3%
8	137	0.3%
9	90	0.2%
Other values (24)	231	0.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	45816	86.0%
1	3048	5.7%
2	1509	2.8%
3	990	1.9%
4	559	1.0%
5	433	0.8%
6	260	0.5%
7	184	0.3%
8	137	0.3%
9	90	0.2%

Value	Count	Frequency (%)
48	1	< 0.1%
44	1	< 0.1%
42	1	< 0.1%
34	1	< 0.1%
29	2	< 0.1%
28	1	< 0.1%
27	1	< 0.1%
26	1	< 0.1%
25	1	< 0.1%
24	3	< 0.1%

rec_online_20_b2
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	23
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3316371557

Minimum	0
Maximum	29
Zeros	46324
Zeros (%)	87.0%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2
Maximum	29
Range	29
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.181725052
Coefficient of variation (CV)	3.563307161
Kurtosis	52.20915257
Mean	0.3316371557
Median Absolute Deviation (MAD)	0
Skewness	5.912989462
Sum	17662
Variance	1.396474098
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=23)

Value	Count	Frequency (%)
0	46324	87.0%
1	3046	5.7%
2	1513	2.8%
3	857	1.6%
4	536	1.0%
5	312	0.6%
6	250	0.5%
7	154	0.3%
8	81	0.2%
9	52	0.1%
Other values (13)	132	0.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	46324	87.0%
1	3046	5.7%
2	1513	2.8%
3	857	1.6%
4	536	1.0%
5	312	0.6%
6	250	0.5%
7	154	0.3%
8	81	0.2%
9	52	0.1%

Value	Count	Frequency (%)
29	1	< 0.1%
26	1	< 0.1%
22	1	< 0.1%
20	1	< 0.1%
19	2	< 0.1%
17	3	< 0.1%
16	4	< 0.1%
15	8	< 0.1%
14	7	< 0.1%
13	17	< 0.1%

chip_pre_rec_10
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	416.2 KiB

	52526
	731

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	52526	98.6%
	731	1.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	52526	98.6%
	731	1.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

chip_pre_rec_20
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	416.2 KiB

	53005
	243
	8
	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Common Values

Value	Count	Frequency (%)
	53005	99.5%
	243	0.5%
	8	< 0.1%
	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	53005	99.5%
	243	0.5%
	8	< 0.1%
	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

rec_online_13
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	23
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.09534896821

Minimum	0
Maximum	42
Zeros	50701
Zeros (%)	95.2%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	42
Range	42
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.6324765806
Coefficient of variation (CV)	6.633281853
Kurtosis	657.1545204
Mean	0.09534896821
Median Absolute Deviation (MAD)	0
Skewness	17.96037187
Sum	5078
Variance	0.400026625
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=23)

Value	Count	Frequency (%)
0	50701	95.2%
1	1568	2.9%
2	434	0.8%
3	232	0.4%
4	138	0.3%
5	60	0.1%
6	43	0.1%
7	27	0.1%
8	17	< 0.1%
9	10	< 0.1%
Other values (13)	27	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	50701	95.2%
1	1568	2.9%
2	434	0.8%
3	232	0.4%
4	138	0.3%
5	60	0.1%
6	43	0.1%
7	27	0.1%
8	17	< 0.1%
9	10	< 0.1%

Value	Count	Frequency (%)
42	1	< 0.1%
28	1	< 0.1%
25	1	< 0.1%
22	1	< 0.1%
21	2	< 0.1%
17	2	< 0.1%
16	1	< 0.1%
15	2	< 0.1%
14	1	< 0.1%
13	3	< 0.1%

rec_online_50_b8
Real number (ℝ_≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.01083425653

Minimum	0
Maximum	11
Zeros	52928
Zeros (%)	99.4%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	11
Range	11
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.1759514914
Coefficient of variation (CV)	16.24029216
Kurtosis	1024.826145
Mean	0.01083425653
Median Absolute Deviation (MAD)	0
Skewness	27.03772441
Sum	577
Variance	0.03095892733
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	52928	99.4%
1	201	0.4%
2	78	0.1%
3	25	< 0.1%
5	9	< 0.1%
6	5	< 0.1%
4	5	< 0.1%
7	3	< 0.1%
8	1	< 0.1%
11	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	52928	99.4%
1	201	0.4%
2	78	0.1%
3	25	< 0.1%
4	5	< 0.1%
5	9	< 0.1%
6	5	< 0.1%
7	3	< 0.1%
8	1	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
11	1	< 0.1%
10	1	< 0.1%
8	1	< 0.1%
7	3	< 0.1%
6	5	< 0.1%
5	9	< 0.1%
4	5	< 0.1%
3	25	< 0.1%
2	78	0.1%
1	201	0.4%

rec_online_30_b4
Real number (ℝ_≥0)

ZEROS

Distinct	13
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.04868843532

Minimum	0
Maximum	12
Zeros	51710
Zeros (%)	97.1%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	12
Range	12
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.3589232183
Coefficient of variation (CV)	7.371837192
Kurtosis	207.9429036
Mean	0.04868843532
Median Absolute Deviation (MAD)	0
Skewness	12.13972265
Sum	2593
Variance	0.1288258767
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
0	51710	97.1%
1	1021	1.9%
2	284	0.5%
3	124	0.2%
4	50	0.1%
5	26	< 0.1%
6	18	< 0.1%
7	12	< 0.1%
8	5	< 0.1%
9	3	< 0.1%
Other values (3)	4	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	51710	97.1%
1	1021	1.9%
2	284	0.5%
3	124	0.2%
4	50	0.1%
5	26	< 0.1%
6	18	< 0.1%
7	12	< 0.1%
8	5	< 0.1%
9	3	< 0.1%

Value	Count	Frequency (%)
12	1	< 0.1%
11	1	< 0.1%
10	2	< 0.1%
9	3	< 0.1%
8	5	< 0.1%
7	12	< 0.1%
6	18	< 0.1%
5	26	< 0.1%
4	50	0.1%
3	124	0.2%

rec_online_40_b6
Real number (ℝ_≥0)

ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.01470229266

Minimum	0
Maximum	10
Zeros	52780
Zeros (%)	99.1%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	10
Range	10
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.1864559261
Coefficient of variation (CV)	12.68209867
Kurtosis	481.2980427
Mean	0.01470229266
Median Absolute Deviation (MAD)	0
Skewness	18.64721571
Sum	783
Variance	0.03476581239
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	52780	99.1%
1	308	0.6%
2	85	0.2%
3	54	0.1%
4	18	< 0.1%
6	6	< 0.1%
5	5	< 0.1%
10	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	52780	99.1%
1	308	0.6%
2	85	0.2%
3	54	0.1%
4	18	< 0.1%
5	5	< 0.1%
6	6	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
10	1	< 0.1%
6	6	< 0.1%
5	5	< 0.1%
4	18	< 0.1%
3	54	0.1%
2	85	0.2%
1	308	0.6%
0	52780	99.1%

pct_rec_1190
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	416.2 KiB

	53142
	107
	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	53142	99.8%
	107	0.2%
	8	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	53142	99.8%
	107	0.2%
	8	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

pct_rec_690
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.004055804871

Minimum	0
Maximum	6
Zeros	53128
Zeros (%)	99.8%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	6
Range	6
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.09445374625
Coefficient of variation (CV)	23.28853317
Kurtosis	1205.386794
Mean	0.004055804871
Median Absolute Deviation (MAD)	0
Skewness	30.75651164
Sum	216
Variance	0.00892151018
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	53128	99.8%
1	71	0.1%
2	37	0.1%
3	17	< 0.1%
6	2	< 0.1%
4	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	53128	99.8%
1	71	0.1%
2	37	0.1%
3	17	< 0.1%
4	2	< 0.1%
6	2	< 0.1%

Value	Count	Frequency (%)
6	2	< 0.1%
4	2	< 0.1%
3	17	< 0.1%
2	37	0.1%
1	71	0.1%
0	53128	99.8%

rec_online_100_b18
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	416.2 KiB

	53234
	18
	3
	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	53234	> 99.9%
	18	< 0.1%
	3	< 0.1%
	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	53234	> 99.9%
	18	< 0.1%
	3	< 0.1%
	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

pct_rec_sos_5
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.0006196368552

Minimum	0
Maximum	7
Zeros	53240
Zeros (%)	> 99.9%
Negative	0
Negative (%)	0.0%
Memory size	416.2 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	7
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.0443984783
Coefficient of variation (CV)	71.65241694
Kurtosis	13895.33239
Mean	0.0006196368552
Median Absolute Deviation (MAD)	0
Skewness	106.1640427
Sum	33
Variance	0.001971224876
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	53240	> 99.9%
1	10	< 0.1%
2	3	< 0.1%
3	2	< 0.1%
4	1	< 0.1%
7	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	53240	> 99.9%
1	10	< 0.1%
2	3	< 0.1%
3	2	< 0.1%
4	1	< 0.1%
7	1	< 0.1%

Value	Count	Frequency (%)
7	1	< 0.1%
4	1	< 0.1%
3	2	< 0.1%
2	3	< 0.1%
1	10	< 0.1%
0	53240	> 99.9%

sos_rec_3
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	416.2 KiB

	53256
	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Common Values

Value	Count	Frequency (%)
	53256	> 99.9%
	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	53256	> 99.9%
	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

rec_online_8
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	416.2 KiB

	53257

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	53257	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	53257	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

venda
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	416.2 KiB

	40490
	12767

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	40490	76.0%
	12767	24.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	40490	76.0%
	12767	24.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values